Everything AI: An Update on Machine Learning & Multiple Expansion

In our June piece External Obsolescence: Tech Investors’ Newest Nightmare, we explained how the consensus view on AI stocks might simply be misplaced confidence that had sent multiples soaring. We highlighted that investors had anointed Microsoft, Apple, Google, Nvidia, and Amazon as the “sure-fire” winners of all things AI. We referred to these five stocks as “MAGNA” for short.

We built a simple chart showing the primary driver of returns was multiple expansion – not fundamentals.

A broker-dealer recently penned an explanation for why AI and tech stocks today “…don’t appear to be in a bubble.”[i] Thoughtful in structure, the piece observed that tech valuations have risen this year despite rising rates and acknowledged this “…suggests investors are assuming much higher future growth rates for these companies.” The work’s rationale for why AI is not a bubble emphasized the following three items:

Big tech’s Price-to-Earnings (P/E) ratios are lower than they were in the dot.com or Nifty 50 manias
The concentrated returns and lack of “broader optimism” are further evidence that we are not in a bubble
Big tech has higher margins, better balance sheets, and better moats than tech in the dot.com bubble[1]

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KCR strongly recommends folks read their thoughtful work. In contrast, this paper will explain:

Why P/E could be a dangerous metric for these stocks and offers an alternative view of tech valuations
Why concentration indicates AI darlings are in a massive bubble
Evidence AI stocks are using the same accounting gimmicks seen before the dot.com bubble imploded

Everyone is busy. Let’s hustle. First up, valuation:

Navy blue line is the price-to-sales ratio of tech stocks. Light blue line is the price-to-sales ratio of the S&P 500. Using this metric instead of price-to-earnings ratios, the story looks familiar. Tech’s valuation is a near-perfect doppelganger for the peak of the dot.com bubble.

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FAQ

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As a reminder for our Financial Advisors: our models are available on a continuous basis, and most have been in production for over a decade. If you are looking for simple, concentrated, low turnover, and tax efficient model portfolios we would like to talk with you. KCR also offers a wide range of easy-to-use but sophisticated tools. Our toolkits can help identify mispriced stocks with the best and worst risk/reward characteristics, estimate a stock’s duration and warn you when a company is engaging in low-quality accounting. Over the last 12 years, KCR has built and offers time-tested and class-leading products built by experienced and proven money managers for fixed to low prices.
Kailash Capital Research, LLC ’s sister company, L2 Asset Management, runs market neutral, long/short, large-cap, and mid-cap long-only portfolios with a value and quality bias. L2 employs a highly disciplined investment process characterized by moderate concentration, low turnover, high tax efficiency, and low fees. While nobody can predict the future, we believe the recent resurgence in risk-adjusted returns seen across all products is the beginning of what may be a long period where speculation is punished, and prudence and patience rewarded.

Sources

[i] https://www.goldmansachs.com/intelligence/pages/why-ai-stocks-arent-in-a-bubble.html

[1] In the piece, they note return on equity (ROE) and margins are nearly double what was seen in the runup to the dot.com peak

[ii] https://www.theglobeandmail.com/report-on-business/the-story-behind-nortels-fall/article20935077/

[iii] https://www.wsj.com/tech/ai/google-commits-2-billion-in-funding-to-ai-startup-anthropic-db4d4c50

[iv] https://pitchbook.com/news/articles/vc-valuations-generative-ai-startups

[v] https://sfstandard.com/2023/07/10/san-francisco-companies-got-half-the-worlds-ai-funding-so-far-this-year/

[vi] https://www.ft.com/content/cf939ea4-d96c-4908-896a-48a74381f251

[vii] https://www.wsj.com/articles/no-business-plan-no-problem-chatgpt-spawns-an-investor-gold-rush-in-ai-6bdbed3c

[viii] https://www.theverge.com/2023/8/8/23824661/coreweave-nvidia-debt-gpu-ai-chips-collateral

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